The 3rd Generation Partnership Project, 3GPP, is responsible for the standardization of the Universal Mobile Telecommunication System, UMTS, and Long Term Evolution, LTE. The 3GPP work on LTE is also referred to as Evolved Universal Terrestrial Access Network, E-UTRAN. LTE is a technology for realizing high-speed packet-based communication that can reach high data rates both in the downlink and in the uplink, and is thought of as a next generation mobile communication system relative to UMTS. In order to support high data rates, LTE allows for a system bandwidth of 20 MHz, or up to 100 MHz when carrier aggregation is employed. LTE is also able to operate in different frequency bands and can operate in at least Frequency Division Duplex, FDD and Time Division Duplex, TDD, modes.
The Channel State Information, CSI, refers to known channel properties of a communication link. This information describes how a signal propagates from the transmitter to the receiver and represents the combined effect of, for example, scattering, fading, and power decay with distance. The CSI makes it possible to adapt transmissions to current channel conditions, which is crucial for achieving reliable communication with high data rates in multi-antenna systems. Feeding back CSI to a transmitter in order for a transmitting eNodeB to optimally utilize sparse radio spectrum for future transmissions is well established prior art. Hereby the eNodeB can select the optimal Modulation and Coding Scheme, MCS, rank and precoding matrix for a packet such that it, with certain likelihood, is correctly received at the receiver after passing through the medium, while still utilizing sparse radio resources efficiently.
A User Equipment, UE, that is moving with some speed in relation to an access point, is exposed to highly varying channel conditions. Since CSI feed-back typically requires processing, and transmission from the UE to the eNodeB and then further processing at the eNodeB, a delay is introduced between the instant of CSI measurement and the instant when the data transmission based on said CSI information actually takes place at the eNodeB.
During that time, channel conditions may have changed substantially thereby rendering the CSI obsolete, in turn resulting in the eNodeB using a suboptimal MCS for its transmissions.
One way of mitigating the time difference between CQI measurement and its use is to apply a channel predictor in order to estimate the future channel. This approach is also well known in the art, but has some disadvantages. When the channel covariance is estimated based on a predicted channel, it will be biased. It is possible to compensate for this bias by scaling the channel power estimate. However, this scaling will increase the noise of the estimate, which is undesirable.
In the paper “Adaptive Modulation Systems for Predicted Wireless Channels”, IEEE Globecom 03, page 357-361, vol 1, Falahati et al. discusses a solution where the channel power is estimated based on a channel predicates. This paper discloses predicting channel power e.g. for the purpose of predicting SNR. Falahati et al. suggests predicting the channel power by squaring the channel prediction and is related to solving the bias problems of such an approach. However, this solution is not always useful, because it may result in a noise amplification that may be undesirable.